def plot (self, ax, *args, **kwargs):
ax.plot (self.xy[:,1], self.xy[:,0], *args, **kwargs)
for xy,cov in zip (self.xy, self.cov):
sig = cov.reshape ((2,2))
draw_covariance (ax, xy, sig, 9., *args, **kwargs)
dy = xy_client[:,1] - xy_server[:,1]
dist = (dy**2.+dx**2.)**(1./2)
print dist
ii_max = np.argmax (dist)
print 'mean norm diff between poses = ', dist.mean ()
print 'max norm diff between poses = ', dist.max ()
# plot it all
fig = plt.figure ()
ax = fig.add_subplot (111)
ax.plot (server_nodes.mu[:,1], server_nodes.mu[:,0], 'b-', lw=0.5)
ax.plot (xy_server[:,1], xy_server[:,0], 'b.-', label='server', lw=2)
for xy,cov in zip (xy_server, cov_server):
sig = cov.reshape ((2,2))
draw_covariance (ax, xy, sig, 9., 'b', lw=2)
#ii = np.where (client_nodes.id > 500)[0]
#ax.plot (client_nodes.mu[ii,1], client_nodes.mu[ii,0], 'r-')
ax.plot (xy_client[:,1], xy_client[:,0], 'r.-', label='client', lw=1)
for xy,cov in zip (xy_client, cov_client):
sig = cov.reshape ((2,2))
draw_covariance (ax, xy, sig, 9., 'r', lw=1)
ax.legend (numpoints=1)
ax.axis ('equal')
ax.grid ()
plt.show ()